Dynamic optimizing scanner for identity and access management (IAM) compliance verification

ABSTRACT

An identity and access management (IAM) system is associated with a set of data sources from which data is collected. A set of vulnerabilities that the IAM system should attempt to detect is identified. For each vulnerability to be detected, a prioritized list of strategies used to detect that vulnerability is generated. Preferably, each strategy specifies the type(s) of data required to detect that vulnerability. An algorithm to determine a best strategy to be used for detecting each vulnerability, preferably based on the data available from the data sources, is then identified. The IAM system then collects data in an optimized manner. In particular, during the collection process, the IAM system preferably collects only what is necessary based on the configuration, even if the data source is capable of providing additional data. The collected data is then processed to detect security vulnerabilities associated with the IAM accounts.

BACKGROUND

Technical Field

This disclosure relates generally to the field of digital resourceaccess, and more particularly to risk-based computer recertification ofonline access.

Background of the Related Art

Identity and Access Management Governance is a set of processes andpolicies for organizations to manage risks and maintain compliance withregulations and policies by administering, securing, and monitoringidentities and their access to applications, information, and systems.Although potentially complex in implementation, the concept of Identityand Access Management (IAM) Governance is fairly straightforward:determine who should have access to what resources and who should not,according to government regulations, industry-specific regulations (SOX,HIPPA, GLBA, etc.), and business regulations and guidelines. Typically,key aspects of IAM Governance include access request governance,entitlement certifications, reports and audits, and analytics andintelligence (including role management, entitlement management,separation of duties enforcement, and privileged identity management).An end-to-end IAM Governance solution may also provide relatedfunctions, such as access enforcement, user provisioning, passwordmanagement, and user lifecycle management.

Identity and access management (IAM) systems protect enterprise data andapplications with context-based access control, security policyenforcement and business-driven driven identity governance. Thesesystems may be operated in a standalone manner, in association withcloud-based environments, or in hybrid environments.

Automated systems for IAM health checking detect identity-centric riskswithin a governance system by scanning for one or more weaknesspatterns, such as too many Admins configured, account sharing, orcloning of access permissions. While detecting these and other suchconditions provides useful information, known detection mechanisms aretime-consuming and require large amounts of data to be read or extractedfrom multiple systems being governed. The problems associated with datacollection in this context are exacerbated by the existence of multipledetection algorithms that may be available for evaluating a particularrisk, and because detection algorithms have different levels ofreliability as well as different data requirements. As a consequence,known IAM health checking techniques tend to operate with missing orimperfect data, or using algorithms that do not always fit the availabledata. Moreover, a best algorithm for a particular job typically cannotbe pre-configured.

Known implementations that require a fixed set of data to detectvulnerabilities are not flexible, and they are incapable of detectingvulnerabilities using different strategies based on available data.

BRIEF SUMMARY

According to this disclosure, an identity and access management (IAM)system is augmented with the ability to execute different types ofdetection mechanisms based on various factors, such as the degree ofreliability desired, the nature of the available data, cost. latency.and the like. In one implementation, the IAM system is associated with aset of data sources from which data is collected. A particular sourcemay provide one or more types of data. A set of vulnerabilities that theIAM system should attempt to detect is identified. For eachvulnerability to be detected, a prioritized list of strategies used todetect that vulnerability is then generated. Preferably, each strategyspecifies the type(s) of data required to detect that vulnerability, aswell as the code to detect it. An algorithm to determine a best strategyto be used for detecting each vulnerability, preferably based on thedata available from the data sources, is then identified. Given thisconfiguration, the IAM system then operates to collect data in anoptimized manner. Thus, preferably each data source required to providedata is called to collect data for all of the configured vulnerabilitiesthat are to be detected. During the collection process, the IAM systemcollects only what is necessary based on the configuration, even if thedata source is capable of providing additional data.

Thus, according to this disclosure a best (or at least better) strategyfor vulnerability detection is chosen based on the data sourcesavailable, and data collection is optimized so that a given data sourcepreferably is invoked only once (or as few times as possible) to collectdata for all vulnerabilities to be detected. In this manner, the IAMsystem operates much more efficiently, as unnecessary data either is notcollected or its collection minimized.

The foregoing has outlined some of the more pertinent features of thesubject matter. These features should be construed to be merelyillustrative. Many other beneficial results can be attained by applyingthe disclosed subject matter in a different manner or by modifying thesubject matter as will be described.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIG. 1 depicts an exemplary block diagram of a distributed dataprocessing environment in which exemplary aspects of the illustrativeembodiments may be implemented;

FIG. 2 is an exemplary block diagram of a data processing system inwhich exemplary aspects of the illustrative embodiments may beimplemented;

FIG. 3 is a representative security identity management system in whichthe disclosed subject matter may be implemented;

FIG. 4 illustrates a step-by step-guide for implementing IAM governanceusing an Identity and Access Management system;

FIG. 5 depicts an IAM system that is enhanced to include an optimizedvulnerability scanner according to this disclosure;

FIG. 6 depicts a high-level process flow of the operation of the IAMsystem;

FIG. 7 depicts representative pseudocode for determining the types ofdata supported by the data sources according to the high-level processflow in FIG. 6;

FIG. 8 depicts representative pseudocode to determine what strategies touse and what types of data to collect according to the high-levelprocess flow in FIG. 6;

FIG. 9 depicts representative pseudocode for collecting the data fromthe data sources according to the high-level process flow in FIG. 6; and

FIG. 10 depicts representative pseudocode for detecting vulnerabilitiesaccording to the high-level process flow in FIG. 6.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

With reference now to the drawings and in particular with reference toFIGS. 1-2, exemplary diagrams of data processing environments areprovided in which illustrative embodiments of the disclosure may beimplemented. It should be appreciated that FIGS. 1-2 are only exemplaryand are not intended to assert or imply any limitation with regard tothe environments in which aspects or embodiments of the disclosedsubject matter may be implemented. Many modifications to the depictedenvironments may be made without departing from the spirit and scope ofthe present invention.

With reference now to the drawings, FIG. 1 depicts a pictorialrepresentation of an exemplary distributed data processing system inwhich aspects of the illustrative embodiments may be implemented.Distributed data processing system 100 may include a network ofcomputers in which aspects of the illustrative embodiments may beimplemented. The distributed data processing system 100 contains atleast one network 102, which is the medium used to provide communicationlinks between various devices and computers connected together withindistributed data processing system 100. The network 102 may includeconnections, such as wire, wireless communication links, or fiber opticcables.

In the depicted example, server 104 and server 106 are connected tonetwork 102 along with storage unit 108. In addition, clients 110, 112,and 114 are also connected to network 102. These clients 110, 112, and114 may be, for example, personal computers, network computers, or thelike. In the depicted example, server 104 provides data, such as bootfiles, operating system images, and applications to the clients 110,112, and 114. Clients 110, 112, and 114 are clients to server 104 in thedepicted example. Distributed data processing system 100 may includeadditional servers, clients, and other devices not shown.

In the depicted example, distributed data processing system 100 is theInternet with network 102 representing a worldwide collection ofnetworks and gateways that use the Transmission ControlProtocol/Internet Protocol (TCP/IP) suite of protocols to communicatewith one another. At the heart of the Internet is a backbone ofhigh-speed data communication lines between major nodes or hostcomputers, consisting of thousands of commercial, governmental,educational and other computer systems that route data and messages. Ofcourse, the distributed data processing system 100 may also beimplemented to include a number of different types of networks, such asfor example, an intranet, a local area network (LAN), a wide areanetwork (WAN), or the like. As stated above, FIG. 1 is intended as anexample, not as an architectural limitation for different embodiments ofthe disclosed subject matter, and therefore, the particular elementsshown in FIG. 1 should not be considered limiting with regard to theenvironments in which the illustrative embodiments of the presentinvention may be implemented.

With reference now to FIG. 2, a block diagram of an exemplary dataprocessing system is shown in which aspects of the illustrativeembodiments may be implemented. Data processing system 200 is an exampleof a computer, such as client 110 in FIG. 1, in which computer usablecode or instructions implementing the processes for illustrativeembodiments of the disclosure may be located.

With reference now to FIG. 2, a block diagram of a data processingsystem is shown in which illustrative embodiments may be implemented.Data processing system 200 is an example of a computer, such as server104 or client 110 in FIG. 1, in which computer-usable program code orinstructions implementing the processes may be located for theillustrative embodiments. In this illustrative example, data processingsystem 200 includes communications fabric 202, which providescommunications between processor unit 204, memory 206, persistentstorage 208, communications unit 210, input/output (I/O) unit 212, anddisplay 214.

Processor unit 204 serves to execute instructions for software that maybe loaded into memory 206. Processor unit 204 may be a set of one ormore processors or may be a multi-processor core, depending on theparticular implementation. Further, processor unit 204 may beimplemented using one or more heterogeneous processor systems in which amain processor is present with secondary processors on a single chip. Asanother illustrative example, processor unit 204 may be a symmetricmulti-processor (SMP) system containing multiple processors of the sametype.

Memory 206 and persistent storage 208 are examples of storage devices. Astorage device is any piece of hardware that is capable of storinginformation either on a temporary basis and/or a permanent basis. Memory206, in these examples, may be, for example, a random access memory orany other suitable volatile or non-volatile storage device. Persistentstorage 208 may take various forms depending on the particularimplementation. For example, persistent storage 208 may contain one ormore components or devices. For example, persistent storage 208 may be ahard drive, a flash memory, a rewritable optical disk, a rewritablemagnetic tape, or some combination of the above. The media used bypersistent storage 208 also may be removable. For example, a removablehard drive may be used for persistent storage 208.

Communications unit 210, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 210 is a network interface card. Communications unit210 may provide communications through the use of either or bothphysical and wireless communications links.

Input/output unit 212 allows for input and output of data with otherdevices that may be connected to data processing system 200. Forexample, input/output unit 212 may provide a connection for user inputthrough a keyboard and mouse. Further, input/output unit 212 may sendoutput to a printer. Display 214 provides a mechanism to displayinformation to a user.

Instructions for the operating system and applications or programs arelocated on persistent storage 208. These instructions may be loaded intomemory 206 for execution by processor unit 204. The processes of thedifferent embodiments may be performed by processor unit 204 usingcomputer implemented instructions, which may be located in a memory,such as memory 206. These instructions are referred to as program code,computer-usable program code, or computer-readable program code that maybe read and executed by a processor in processor unit 204. The programcode in the different embodiments may be embodied on different physicalor tangible computer-readable media, such as memory 206 or persistentstorage 208.

Program code 216 is located in a functional form on computer-readablemedia 218 that is selectively removable and may be loaded onto ortransferred to data processing system 200 for execution by processorunit 204. Program code 216 and computer-readable media 218 form computerprogram product 220 in these examples. In one example, computer-readablemedia 218 may be in a tangible form, such as, for example, an optical ormagnetic disc that is inserted or placed into a drive or other devicethat is part of persistent storage 208 for transfer onto a storagedevice, such as a hard drive that is part of persistent storage 208. Ina tangible form, computer-readable media 218 also may take the form of apersistent storage, such as a hard drive, a thumb drive, or a flashmemory that is connected to data processing system 200. The tangibleform of computer-readable media 218 is also referred to ascomputer-recordable storage media. In some instances,computer-recordable media 218 may not be removable.

Alternatively, program code 216 may be transferred to data processingsystem 200 from computer-readable media 218 through a communicationslink to communications unit 210 and/or through a connection toinput/output unit 212. The communications link and/or the connection maybe physical or wireless in the illustrative examples. Thecomputer-readable media also may take the form of non-tangible media,such as communications links or wireless transmissions containing theprogram code. The different components illustrated for data processingsystem 200 are not meant to provide architectural limitations to themanner in which different embodiments may be implemented. The differentillustrative embodiments may be implemented in a data processing systemincluding components in addition to or in place of those illustrated fordata processing system 200. Other components shown in FIG. 2 can bevaried from the illustrative examples shown. As one example, a storagedevice in data processing system 200 is any hardware apparatus that maystore data. Memory 206, persistent storage 208, and computer-readablemedia 218 are examples of storage devices in a tangible form.

In another example, a bus system may be used to implement communicationsfabric 202 and may be comprised of one or more buses, such as a systembus or an input/output bus. Of course, the bus system may be implementedusing any suitable type of architecture that provides for a transfer ofdata between different components or devices attached to the bus system.Additionally, a communications unit may include one or more devices usedto transmit and receive data, such as a modem or a network adapter.Further, a memory may be, for example, memory 206 or a cache such asfound in an interface and memory controller hub that may be present incommunications fabric 202.

Computer program code for carrying out operations of the presentinvention may be written in any combination of one or more programminglanguages, including an object-oriented programming language such asJava™, Smalltalk, C++ or the like, and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer, or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Those of ordinary skill in the art will appreciate that the hardware inFIGS. 1-2 may vary depending on the implementation. Other internalhardware or peripheral devices, such as flash memory, equivalentnon-volatile memory, or optical disk drives and the like, may be used inaddition to or in place of the hardware depicted in FIGS. 1-2. Also, theprocesses of the illustrative embodiments may be applied to amultiprocessor data processing system, other than the SMP systemmentioned previously, without departing from the spirit and scope of thedisclosed subject matter.

As will be seen, the techniques described herein may operate inconjunction within the standard client-server paradigm such asillustrated in FIG. 1 in which client machines communicate with anInternet-accessible Web-based portal executing on a set of one or moremachines. End users operate Internet-connectable devices (e.g., desktopcomputers, notebook computers, Internet-enabled mobile devices, or thelike) that are capable of accessing and interacting with the portal.Typically, each client or server machine is a data processing systemsuch as illustrated in FIG. 2 comprising hardware and software, andthese entities communicate with one another over a network, such as theInternet, an intranet, an extranet, a private network, or any othercommunications medium or link. A data processing system typicallyincludes one or more processors, an operating system, one or moreapplications, and one or more utilities. The applications on the dataprocessing system provide native support for Web services including,without limitation, support for HTTP, SOAP, XML, WSDL, UDDI, and WSFL,among others. Information regarding SOAP, WSDL, UDDI and WSFL isavailable from the World Wide Web Consortium (W3C), which is responsiblefor developing and maintaining these standards; further informationregarding HTTP and XML is available from Internet Engineering Task Force(IETF). Familiarity with these standards is presumed.

Identity and Access Management

As used herein, an “account” typically refers to an entity that containsa set of parameters that define application-specific attributes of aprincipal, which include the identity, user profile, and credentials.

“Access” refers the ability to read, update, delete, or otherwise use aresource. Access to protected resources is typically controlled bysystem software.

A “credential” refers to a declaration of authorization or othersecurity attributes of a subject that is typically validated and signedby a trusted third party. Typically, a credential represents the ID andauthenticators (such as a password) for a resource.

An “entitlement” refers to a capability-based reason that a user isgiven a permission or set of permissions to access IT resources(services).

An “identity” refers to a subset of profile data that uniquelyrepresents a person or entity and that is stored in one or morerepositories.

A “dormant account” is an account that has not been used for a given,preferably configurable-time period (e.g., a number of days). A dormantaccount typically is associated with a service. Preferably, servers inthe system are configured to record last login information, and toprovide (return) this information upon request. By reconciling the lastlogin information, the system can determine the existence of dormantaccounts.

An “orphan account” is an account on a managed resource, an accountwhose owner cannot be automatically determined by the system.

An “ownership type” refers to a category that classifies ownership ofaccounts. One account preferably can have only one type of ownership.Accounts can be marked with different ownership types depending on theiruse. Default ownership types include, for example, device, personal,system, and vendor.

A “person” is an individual in the system that has a person record inone or more corporate directories.

A “policy” is a set of considerations that influence the behavior of amanaged resource or a user.

A “principal” is a person or group that has been granted permissions. Italso refers to an entity that can communicate securely with anotherentity.

A “recertification” refers to the process of validating and possiblyupdating credentials with a system, typically after a specified timeinterval. A “recertification policy” refers to a policy that defines thelife cycle rule for automatically validating accounts and users in aprovisioning system at a specified frequency. The policy sends approvalsto the recertification policy participants asking if the accounts orusers are still certified to use the managed resource for which theaccount was provisioned.

In identity management, “provisioning” refers to the process ofproviding, deploying, and tracking a service or component. To“provision” means to set up and maintain the access of a user to asystem, or to create an account on a managed resource.

A “provisioning policy” is a policy that defines the access to variousmanaged resources (services), such as applications or operating systems.Access is granted to all users, users with a specific role, or users whoare not members of a specific role.

A “resource” is a hardware, software, or data entity.

A “role” is a logical group of principals that provide a set ofpermissions. Access to resources is controlled by using a provisioningpolicy to grant access to a role. A role can also represent a group ofprincipals based on business job title or other business-relatedattributes.

A “service” is a representation of a managed resource, application,database, or system. In an identity management system, typically aservice represents the user repository for a managed resource.

A “user” is an individual, organization, process, device, program,protocol, or system that uses the services of a computing system. Forexample, a user is an individual who uses the identity management systemto manage their accounts and passwords, or that is managed by thesystem.

For many applications, networks, databases and other resources, usersare given “access” by an authority or administrative role to enableactivity associated with the resource. The conditions and limitations ofthe access for a given user are referred to as the “access entitlement”of the user, and include defined limitations as to the activities theuser may perform with or on the resource. Access entitlements amongusers of the same resource can vary. For instance, a databaseadministrator may have access and authority to read, write, edit,search, copy, delete and transfer data for a specific database, whereasothers with access to the database may be limited to searching andreading data.

Identity management (IdM) is an administrative area that utilizes asystem to identify individuals with membership or association, such aswith a group, organization, company, etc. Additionally, an IdM systemcontrols the individual's access to resources by use of restrictions orpermissions. To facilitate better decisions for granting appropriateaccess, information regarding a user's request for access, their jobrole, and whether the access is a new request or renewal is considered,however, this limited information can prove ineffective in preventinghigh risk situations.

Control and oversight of resource access approval of individuals inbusiness or enterprise organizations are further challenged by theturnover of personnel, the dynamic day-to-day changes and organizationalrestructuring, as well as application version upgrades. In largeorganizations, granting users the appropriate access entitlements toresources and maintaining access entitlements is a difficult task thatcan involve thousands of users and hundreds of resources. Resourceaccess decisions and compliance verification responsibilities aretypically allocated to supervisors or managers, who have few tools tofacilitate decisions or identify risks and due to time constraints,often provide access in the belief that the individuals' performancewill improve or not be impacted.

It is known in the prior art to provide software and services to deploypolicy-based provisioning solutions. These solutions help companiesautomate the process of provisioning employees, contractors, andbusiness partners with access rights to the applications they need,whether in a closed enterprise environment or across a virtual orextended enterprise. A known product of this type is IBM® SecurityIdentity Manager.

FIG. 3 is a block diagram of this commercially-available identitymanager solution. In one embodiment, as will be described, thetechniques of this disclosure may be implemented in such a solution.This identity manager solution, however, is merely representative andshould not be taken to limit this disclosure. The representativecommercial implementation is known as IBM® Security Identity Manager,Version 6.0. That product manages the identity records that representpeople in a business organization. In particular, the product is anidentity management solution that centralizes the process ofprovisioning records, such as provisioning accounts on operatingsystems, applications, etc., to users. Among other features, the productaffords an organization the ability to add business processes andsecurity policies to basic user management. As will be described in moredetail below, the solution also affords the ability to add approvals foruser requests for access. In general, the solution provides a uniformway to manage user accounts and to delegate administration, includingself-service and a help desk user interface.

As illustrated in FIG. 3, the main components of the IBM® SecurityIdentity Manager solution 300 include IBM Security Identity ManagerServer 302 and required and optional middleware components, includingadapters that provide an interface to managed resources. In a clusterconfiguration as illustrated, the components include a database server304 that stores transactional and historical data, and a relationaldatabase 306 that maintains current and historical states of data.Computers that communicate with the database typically require a Java™Database Connectivity (JDBC) driver 308. For example, a JDBC driverenables an IBM Security Identity Manager Server to communicate with adata source. IBM Security Identity Manager supports a JDBC type 4 driverto connect a Java-based application to a database. The supporteddatabase products are IBM DB2® Database, Oracle DB, and MS SQL Serverdatabase. As also seen in FIG. 3, the solution also includes a directoryserver 310 to store a current state of the managed identities (includinguser account and organizational data) in an LDAP (or equivalent)directory. Thus, for example, IBM Security Identity Manager supports thefollowing products: IBM Tivoli® Directory Server, and Sun EnterpriseDirectory Server. The solution also preferably includes a directoryintegrator 312, such as IBM Tivoli Directory Integrator, to synchronizeidentity data in different directories, databases, and applications. IBMTivoli Directory Integrator synchronizes and manages informationexchanges between applications or directory sources. The solution alsoincludes one or more application servers 314, such as IBM WebSphere®Application Server. WebSphere Application Server runs a Java virtualmachine (JVM) that provides a runtime environment for the applicationcode. The application server provides communication security, logging,messaging, and Web services. As also seen in FIG. 3, typically theconfiguration includes one or more WebSphere Application Servers and adeployment manager that manages the cluster. The solution also typicallyincludes an HTTP server and WebSphere Web Server plug-in 316. An HTTPserver provides administration of IBM Security Identity Manager througha client interface in a web browser. Finally, the solution typicallyincludes one or more IBM Security Identity Manager adapters 318. Anadapter is a program that provides an interface between a managedresource and the IBM Security

Identity Manager Server. Adapters function as trusted virtualadministrators on the target platform for account management. Forexample, adapters do such tasks as creating accounts, suspendingaccounts, and modifying account attributes. An IBM Security IdentityManager adapter can be either agent-based or agentless. An agent-basedadapter is one wherein the user installs adapter code directly onto themanaged resource with which it is designed to communicate. An agentlessadapter is deployed onto the IBM Security Identity Manager Server andthe system that hosts IBM Tivoli Directory Integrator. In this case, theadapter code is separate from the managed resource with which it isdesigned to communicate.

As noted above, the implementation shown in FIG. 3 is not intended to belimiting but, rather, merely illustrates one possible operatingenvironment; other commercial or proprietary implementations may includesimilar components and functionalities.

Each of the machines shown in FIG. 3 may be implemented using themachine architecture shown in FIG. 2; the various machines may interactwith one another as illustrated in FIG. 1.

The security identity management solution of this type also may beimplemented in whole or in part in a cloud-based solution.

FIG. 4 illustrates a representative step-by step-guide for implementingIAM governance using an Identity and Access Management system 400 suchas IBM Security Identity Manager. In this embodiment, an end-to-endsolution is provided in association with several other systems includinga Security Information and Event Management (SIEM) software system 402(e.g., IBM QRadar®), and an access and entitlement enforcement system(e.g., IBM® Security Access Manager) 404.

At step (1), the enterprise identifies the resources that it wantsprotected and the accesses it wants certified and monitored. The data iscleaned, filtered, and prepared for loading into the Identity and AccessManagement system 400 through one or more known mechanisms, or an API.At step (2), the data may be loaded into a role and policy module 402for modeling and management. This data can come from various sources:Human Resources (HR), a planning and modeling tool, or manual entry. Ina typical use case, the data gathered during planning is saved (e.g., ina standard CSV file) and then imported into IBM Security IdentityManager for role and policy modeling. The system can export the modeledrole and entitlement data (e.g., in XML format) and load it forlifecycle management and certification. At step (3), stakeholders andparticipants can use the Identity and Access Management system 400 forthe various tasks that they must perform, such as requesting accessesand roles, approving access and role requests, certifying, managing, andmodeling roles, and reviewing and certifying roles and entitlements. Thecertification data can be used to clean, adapt, and evolve the system.At step (4), the access and entitlement enforcement system 404 importsor provisions the data from Identity and Access management system 400into the access and entitlement enforcement systems. At step (5), theenforcement system 404 uses the certified data for runtime enforcement.The SIEM system 402 monitors actual user activity and provides feedbackto fine-tune access policy planning, administration, and enforcement.

As illustrated in FIG. 4, one of the responsibilities of the Identityand Access Management system 400 is to provide initial and periodicaccess certification for continued business needs to help direct andcontrol operations. Access certification typically includes review andcertification of user access assignment via role or direct assignment todetermine who received access to what, when, and why. It ensures thatusers have only the privileges and exception entitlements they need toperform their job. Access certification can also be used to detectpolicy violations, access anomalies, and orphan and dormant accounts.The IAM system typically also maintains certification and access changehistory, which aids the certification and audit processes.

Vulnerability Scanning in an IAM System

An IAM system may include an application known as a vulnerabilityscanner. A vulnerability scanner detects security vulnerabilities inapplication usage or configuration. For example, the vulnerabilityscanner might detect Microsoft Office 365 accounts that are associatedwith a Company, even though the owner of the account is no longeremployed by the Company. Or, the vulnerability scanner might detectSalesforce.com administrator accounts that were provisioned outside ofthe Company's approved process. This is a so-called “out of process”assignment. The above are merely representative IAM vulnerabilities thata vulnerability scanner of this type might detect.

An IAM vulnerability scanner provides a configuration tool that allows auser to specify a set of sources from which to collect data. A datasource might be a live system (e.g., Salesforce.com), or it might bestatic, such as a log file. Some live data sources provide applicationprogramming interfaces (APIs) that the vulnerability scanner can invoketo determine what type (s) of data the source can provide. For othercases, the type(s) of data provided by live and static sources can bedetermined, typically based on the specific type. Thus, for example, acloud application (e.g., Office 365) might identify the type(s) of dataavailable. Or, the type(s) of data contained in static log files mightbe determined, for example, using a file naming convention or headerinformation. As will be described below, the technique of thisdisclosure assumes it is possible to determine the type(s) of datasupported by each source without actually collecting the data.

By way of further background, consider one type of vulnerabilitydetection referenced above, namely, out of process assignment. In thisexample, suppose that a Company running Salesforce.com (or some othercloud application) having an IAM system with vulnerability scanner hasimplemented what might be considered a “best practice.” According tothis practice, assume that an employee must submit a request foradministrator access to the cloud application, which must be approved bya manager, before a centralized provisioning agent invokes a cloudapplication API to create the new administrator account, or update theemployee's existing Salesforce.com account to give it administrativeprivileges. To detect an out of process assignment in this case, thevulnerability scanner would have to collect the following types of data:a list of accounts from Salesforce.com, including account attribute(s)that indicate whether the account has administrative privileges, as wellas attribute(s) facilitating ownership correlation; audit records froman account approval system, indicating who submitted each request, whoapproved each request, and when the activity occurred; and a list ofemployees, e.g., from the Company's HR system, so that theSalesforce.com accounts can be correlated to an owner, and so that theapproval system audit records can be correlated to people. Based onthese data sources, an out of process assignment would be detected, forexample, if all of the following conditions are met: a givenSalesforce.com account has administrative privileges, ownership of theSalesforce.com administrative account is correlated to a person in theHR system, and there is no approval system audit record indicating thatthe account owner's manager approved a request for the Salesforce.comadministrative privileges.

As another example scenario, assume another Company has not implementedthe “best practice” described above. In particular, suppose that,instead of having an approval process, the Company has a centralizedidentity management system through which all provisioning actions aresupposed to occur. To detect an out of process assignment in this case,the vulnerability scanner would have to collect the following types ofdata: a list of accounts from Salesforce.com, including accountattribute(s) that indicate whether the account has administrativeprivileges, as well as attribute(s) facilitating ownership correlation;audit records from the centralized identity management system, showingwhen each account was created with administrator privileges, or updatedto include administrator privileges; and a list of employees from theCompany's HR system so that the Salesforce.com accounts can becorrelated to an owner, and so that the centralized identity managementaudit records can be correlated to people. In this scenario, the out ofprocess assignment would be detected, for example, if all of thefollowing conditions are met: a Salesforce.com account has administratorprivileges, ownership of the Salesforce.com administrative account iscorrelated to a person in the HR system, and there is no audit recordfrom the centralized identity management system indicating that itcreated the Salesforce.com account with administrative privileges, orupdated the Salesforce.com account to give it administrative privileges.

As yet another example, scenario, assume that the Company does not havean approval process, and that it uses a centralized identity managementsystem that does not audit detailed privilege information. Rather,perhaps the centralized identity management system simply audits thatthe privileges are specified or changed. To detect an out of processassignment in this example, the vulnerability scanner would have tocollect the following types of data: a list of accounts fromSalesforce.com, including account attribute(s) that indicate whether theaccount has administrative privileges, as well as attribute(s)facilitating ownership correlation; audit records from the centralizedidentity management system showing when each account was created orupdated, including whether the privileges were changed; and a list ofemployees from the Company's HR system so that the Salesforce.comaccounts can be correlated to an owner, and so that the centralizedidentity management system audit records can be correlated to people. Inthis example scenario, the out of process assignment would be detected,for example, if all of the following conditions are met: aSalesforce.com account has administrator privileges, ownership of theSalesforce.com administrative account is correlated to a person in theHR system, and there is no audit record from the centralized identitymanagement system indicating that the privileges were specified orchanged.

As the above examples illustrate, the reliability or confidence level ofthe vulnerability degrades with each configuration. That is, (in thefirst scenario) if the criteria for detecting the vulnerability for theCompany using the “best practice” approach are met, it is highly likelythat the account was given administrative privileges outside of theprocess. Further, in this scenario if the criteria for the “bestpractice” approach are not met, it is highly unlikely that the accountrepresents an out of process assignment. In the third scenario, however,if the Company using the centralized identity management system has“weak” auditing, the results produced are of lower confidence. Forexample, the vulnerability would not be detected if the centralizedidentity management system updated the account to include somenon-administrative privileges, but someone also went directly toSalesforce.com (i.e., not through the centralized identity managementsystem) and updated the account to include administrator privileges. Inthis case, the vulnerability scanner would not detect the vulnerability.

Dynamic Optimizing Scanner for IAM Compliance Verification

With the above as background, the subject matter of this disclosure isnow described. As described above, and according to this disclosure, anidentity and access management system is augmented (i.e. extended orsupplemented) to include a vulnerability scanner that is optimizedaccording to the techniques that are now described. In oneimplementation, the vulnerability scanner is an application, e.g.computer program instructions executed in one or more processors. Thevulnerability scanner may be implemented using co-locatedfunctionalities, or using functions that are distributed across multiplemachines (and physical locations). The vulnerability scanner may be astandalone process, it may be network-accessible, or a hybrid ofstandalone and network-accessible components or functions.

As depicted in FIG. 5, an IAM system 500 includes a vulnerabilityscanner application 502. The vulnerability scanner 502 is associatedwith a set of data sources 504. The identity of those data sources maybe pre-configured or otherwise determined by the IAM system or specifiedby the user. It is assumed that a data source 504 (and typically eachdata source) provides one or more types of data. Thus, for example, asource might be “live” (e.g., an application providing one or more APIsfor retrieving data), “static” (e.g., a log file), or some combination.Typically, the type(s) of data provided by a particular one of the datasources 504 can be determined without incurring the overhead ofcollecting the data produced by that source. The vulnerability scanner502 is operative to detect security vulnerabilities, e.g., inapplication usage or configuration. As described above, thevulnerability scanner may be configured to detect when cloud accountsare associated with the Company but the owner of the account is nolonger employed. Or, the scanner might be configured to detectadministrator accounts that have been provisioned outside of theCompany's approved process. These are just representative examples, asthe nature and type of vulnerability detection provided by thevulnerability scanner may be varied. Thus, it is assumed that there area set of vulnerabilities that exist, and the nature and type(s) of thosevulnerabilities may be determined by the system or otherwise specifiedby a permitted user. The vulnerability scanner 502 thus is configured toattempt to detect those one or more vulnerabilities.

According to this disclosure, for each type of vulnerability, preferablythe IAM system 500 defines a prioritized list of strategies that will beused to detect that vulnerability. Preferably, each strategy specifiesthe type(s) of data required to detect the vulnerability, as well as thecode to detect it. An algorithm for determining the best (or, at least abetter or preferred) strategy to be used for detecting a particular (andpreferably each) vulnerability is then implemented. Preferably, thealgorithm implemented is based on the data available from the datasources. According to this technique, preferably data is collected foruse by the vulnerability scanner in a manner that, with respect to thedata collection requirements, is highly-efficient. In this approach forcollecting the data, preferably each data source is called just once tocollect data for all of the configured vulnerabilities, collecting onlywhat is necessary even if the data source is capable of providingadditional data.

FIG. 6 depicts the high level process flow of this technique. Theprocess begins at step 600 by determining the types of data supported bythe sources. At step 602, and based on the types of data as determinedin step 600, the process determines what strategies to use and whattypes of data to collect. At step 604, and based on the strategies asdetermined in step 602, the process continues by collecting the data. Atstep 606, and based on the data collected, the process continues todetect the vulnerabilities. Each of these steps are described in moredetail below.

FIG. 7 depicts representative pseudocode (© IBM 2015, all rightsreserved) for a representative routine to determine the types of datasupported by the sources (step 600 in FIG. 6). The routine begins atstep 700 to initialize to “empty” of a MAP of a SET of types ofsupported data by source. At step 702, a SET of types of supported dataacross all data sources is initialize to “empty.” The MAP and SET areeach a data structure, such as a data array, a linked list, or the like.Then, a loop is initiated for each data source that includes thefollowing steps. At step 704, the routine gets the SET of types ofsupported data for the current source. A test is then performed at step706 to determine if the SET of types of supported data for the currentsource is not empty. If the outcome of the test at step 706 is positive,the routine executes an inner processing loop; in particular, at step708 the SET of types of supported data for the current source is storedin the MAP of SET of types of supported data by source, using thecurrent source as a key. At step 710, the SET of types of supported datafor the current source is then added to the SET of types of supporteddata across all sources. The inner loop initiated at step 706 is thenexited, followed by exit of the loop initiated for each data source.This completes the processing.

FIG. 8 depicts representative pseudocode routine to determine whatstrategies to use and what types of data to collect. This is step 602 inFIG. 6.

The routine begins at step 800 to initialize to empty a SET ofstrategies to use. At step 802, a SET of types of data to collect isinitialized to empty. The SET of strategies and the SET of types of dataare data structures. A loop is then carried out for each type ofvulnerability. This loop is initiated at step 804. In particular, foreach strategy (in priority order) for the current type of vulnerability,the routine gets the SET of types of required data for the currentstrategy at step 806. At step 808, a test is executed to determine ifthe SET of types of required data for the current strategy is empty. Ifthe strategy does not require any data, the strategy is used. This isstep 810. At step 812, the current strategy is added to the SET ofstrategies to use. The “for each strategy” loop is then exited at step814. If the SET of types of required data for the current strategy isnot empty, a test is executed at step 815 to determine if the SET oftypes of required data for the current strategy is a subset of the SETof types of supported data across all sources. If the test at step 815is true, the routine continues at step 816 to add the current strategyto the SET of strategies to use. At step 818, the routine adds the SETof types of required data for the current strategy to the SET of typesof data to collect. The “for each strategy” loop is then exited at step820. The above-described processing is carried out for each type ofvulnerability.

As also depicted in FIG. 8, another data set, namely, a MAP of SET oftypes of data to collect by source, is then initialized to empty. Thisis step 822. A test is then performed at step 824 to determine if theSET of types of data to collect is not empty. If not, then the followingprocessing is carried out for each source in the MAP of SET of types ofsupported data by source. At step 826, the routine gets the SET of typesof supported data for the current source from the MAP of SET of types ofsupported data by source. At step 828, the routine gets the intersectionof the SET of types of supported data for the current source and the SETof types of data to collect. At step 830, the routine stores theintersection in the MAP of SET of types of data to collect by source,using the current source as the key. All sources in the MAP of SET oftypes of supported data by source are processed in this manner.

FIG. 9 depicts representative pseudocode for the function of collectingthe data from the data sources. This is step 604 in FIG. 6. The routinebegins at step 900 by initializing a data structure, the collected data,to empty. For each data source in the MAP of SET of types of data tocollect by source, the process then carries out the following processingsteps. At step 902, the routine gets the SET of types of data to collectfrom the current source from the MAP of SET of types of data to collectby source. At step 904, the routine retrieves the SET of types of datato collect from the current source. The routine then adds the retrieveddata to the collected data at step 906. The routine exits the loop aftereach source in the MAP of SET of types of data to collect by source isprocessed in this manner. This completes the processing.

Finally, FIG. 10 depicts representative pseudocode to detectvulnerabilities, which is step 606 in FIG. 6. The routine is operativefor each strategy in the SET of strategies to use. To this end, at step1000, the routine invokes the strategy to detect vulnerabilities giventhe collected data. The processing loop is then exited once eachstrategy is processed in this manner. This completes the processing.

The data structures and functions represented by the pseudocode aremerely representative of one embodiment. Other data structures orfunctions may be used, or given data structures and functions identifiedmay be combined in whole or in part.

The vulnerability scanner may be configured using a configurator orother provisioning interface (e.g., a set of web pages, a command line,a programmatic interface, or the like).

The technique of this disclosure provides significant advantages. Itenables the IAM system to dynamically choose the best strategy forvulnerability detection based on the data available. Further, thetechnique optimizes the data collection so that a given data source isinvoked preferably only once to collect data for all vulnerabilities. Inthis manner, no unnecessary data is collected, thereby enhancing theperformance and operation of the IAM system in general and thevulnerability scanner in particular. By aggregating multiple datasources for real-time analysis in this manner, the ability of theoverall IAM system to detect vulnerabilities in application usage andconfiguration is optimized, and the technique overcomes the noteddeficiencies of the prior art.

Preferably, for each type of vulnerability, only a highest prioritystrategy for which the required types of data are available are used.The notion of “highest” need not be based on any absolute requirement,but it may also be “relative” to some other value. Preferably, data iscollected only from sources capable of providing the types of datarequired by the selected strategies. Thus, if a source exists that onlyprovides data relevant to unselected lower-priority strategies, thesource is not contacted (at step 604) to collect data. Preferably, instep 604 a source is contacted once to collect data for all of theselected strategies, rather than once each selected strategy. Further,when a source is contacted to collect data, it is instructed to collectonly the types of data required by the selected strategies. If thesource also is capable of collecting other types of data not required bythe selected strategies, preferably it is instructed not to collectthose additional types of data. Further, preferably a source is neverasked to collect data that it is not capable of providing.

In this manner, the technique of this disclosure provides that, withrespect to a particular vulnerability to be detected by the scanner, a“best” (i.e. most reliable or most accurate) strategy is selected. Thenotion of “best” in this context need not be based on any absolute oroptimal requirement, but it may also be “relative” to some other value.As used herein, the approach also is said to be “dynamic,” in partbecause it is based on the data that can and should be collected tosupport a detection strategy and before that data collection actuallyoccurs. In this way, the collection of data is optimized so that onlythe required data is collected from only the required sources.

Additionally, when the tool is implemented in a cloud or othernetwork-accessible manner (e.g., software-as-a-service), preferably the“best” strategy is selected for each user (e.g., a customer) based onthe sources available in the user's operating environment. Inparticular, the strategy used for one customer to detect a particularvulnerability may be different than that used for another customerhaving different sources of data at the latter's disposal. Further, asthe data sources in a given customer's operating environment changeand/or update over time (e.g., based on new products, product upgrades,product deprecation, changes in business process, etc.), the algorithmautomatically adjusts to adopt the “best” strategy based on the user'sthen-current operating configuration.

More generally, the functionality described above may be implemented asa standalone approach, e.g., one or more software-based functionsexecuted by a hardware processor (or multiple such processors), or itmay be available as a managed service (including as a web service via aSOAP/XML interface). The particular hardware and software implementationdetails described herein are merely for illustrative purposes are notmeant to limit the scope of the described subject matter.

More generally, computing devices within the context of the disclosedsubject matter are each a data processing system (such as shown in FIG.2) comprising hardware and software, and these entities communicate withone another over a network, such as the Internet, an intranet, anextranet, a private network, or any other communications medium or link.The applications on the data processing system provide native supportfor Web and other known services and protocols including, withoutlimitation, support for HTTP, FTP, SMTP, SOAP, XML, WSDL, UDDI, andWSFL, among others. Information regarding SOAP, WSDL, UDDI and WSFL isavailable from the World Wide Web Consortium (W3C), which is responsiblefor developing and maintaining these standards; further informationregarding HTTP, FTP, SMTP and XML is available from Internet EngineeringTask Force (IETF). Familiarity with these known standards and protocolsis presumed.

The scheme described herein may be implemented in or in conjunction withvarious server-side architectures including simple n-tier architectures,web portals, federated systems, and the like. The techniques herein maybe practiced in a loosely-coupled server (including a “cloud”-based)environment. In particular, vulnerability scanner functions (orcomponents thereof) may be hosted in the cloud.

Still more generally, the subject matter described herein can take theform of an entirely hardware embodiment, an entirely software embodimentor an embodiment containing both hardware and software elements. In apreferred embodiment, the function is implemented in software, whichincludes but is not limited to firmware, resident software, microcode,and the like. Furthermore, as noted above, the identity context-basedaccess control functionality can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any apparatus thatcan contain or store the program for use by or in connection with theinstruction execution system, apparatus, or device. The medium can be anelectronic, magnetic, optical, electromagnetic, infrared, or asemiconductor system (or apparatus or device). Examples of acomputer-readable medium include a semiconductor or solid state memory,magnetic tape, a removable computer diskette, a random access memory(RAM), a read-only memory (ROM), a rigid magnetic disk and an opticaldisk. Current examples of optical disks include compact disk—read onlymemory (CD-ROM), compact disk—read/write (CD-R/W) and DVD. Thecomputer-readable medium is a tangible item.

The computer program product may be a product having programinstructions (or program code) to implement one or more of the describedfunctions. Those instructions or code may be stored in a computerreadable storage medium in a data processing system after beingdownloaded over a network from a remote data processing system. Or,those instructions or code may be stored in a computer readable storagemedium in a server data processing system and adapted to be downloadedover a network to a remote data processing system for use in a computerreadable storage medium within the remote system.

In a representative embodiment, the vulnerability scanner is implementedin a special purpose computer, preferably in software executed by one ormore processors. The software is maintained in one or more data storesor memories associated with the one or more processors, and the softwaremay be implemented as one or more computer programs. Collectively, thisspecial-purpose hardware and software comprises the functionalitydescribed above.

While the above describes a particular order of operations performed bycertain embodiments of the invention, it should be understood that suchorder is exemplary, as alternative embodiments may perform theoperations in a different order, combine certain operations, overlapcertain operations, or the like. References in the specification to agiven embodiment indicate that the embodiment described may include aparticular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic.

Finally, while given components of the system have been describedseparately, one of ordinary skill will appreciate that some of thefunctions may be combined or shared in given instructions, programsequences, code portions, and the like.

The techniques herein provide for improvements to another technology ortechnical field, namely, identity access and management systems, as wellas improvements to the functioning of data collection and vulnerabilityscanners within such systems.

Having described our invention, what we claim is as follows.

1. A method to facilitate detection of security vulnerabilities inaccounts provisioned in an identity and access management (IAM) system,comprising: determining types of data supported by a set of datasources; based on the types of data supported by the set of datasources, determining a set of one or more vulnerability detectionstrategies to apply to detect the security vulnerabilities; based on theset of one or more vulnerability detection strategies, collecting datafrom the data sources, wherein during data collection a given datasource of the set of data sources is invoked just once to collect datafor all of the set of one or more vulnerability detection strategies;based on the data collected, executing the set of one or morevulnerability detection strategies; and updating at least onevulnerability detection strategy as the set of data sources is changedor updated.
 2. The method as described in claim 1 wherein first andsecond data sources of the set of data sources provide distinct types ofdata from one another.
 3. The method as described in claim 1 wherein thetypes of data include one of: live data, static data, and a combinationof live and static data.
 4. The method as described in claim 1 whereindetermining a set of one or more vulnerability detection strategiesdetermines a strategy for vulnerability detection that, relative to atleast one other strategy for vulnerability detection, is optimized basedon the types of data supported by the set of data sources.
 5. The methodas described in claim 1 wherein determining a set of one or morevulnerability detection strategies determines a strategy forvulnerability detection that, relative to at least one other strategyfor vulnerability detection, is optimized based on an operatingenvironment in which the security vulnerabilities are to be detected. 6.The method as described in claim 1 wherein the IAM system is associatedwith a multi-tenant cloud compute environment, and wherein avulnerability detection strategy for a first tenant is distinct from avulnerability detection strategy for a second tenant.
 7. An apparatus,comprising: a processor; computer memory holding computer programinstructions executed by the processor to facilitate detection ofsecurity vulnerabilities in accounts provisioned in an identity andaccess management (IAM) system, the computer program instructionsoperative to: determine types of data supported by a set of datasources; based on the types of data supported by the set of datasources, determine a set of one or more vulnerability detectionstrategies to apply to detect the security vulnerabilities; based on theset of one or more vulnerability detection strategies, collect data fromthe data sources, wherein during data collection a given data source ofthe set of data sources is invoked just once to collect data for all ofthe set of one or more vulnerability detection strategies; based on thedata collected, execute the set of one or more vulnerability detectionstrategies; and update at least one vulnerability detection strategy asthe set of data sources is changed or updated.
 8. The apparatus asdescribed in claim 7 wherein first and second data sources of the set ofdata sources provide distinct types of data from one another.
 9. Theapparatus as described in claim 7 wherein the types of data include oneof: live data, static data, and a combination of live and static data.10. The apparatus as described in claim 7 wherein the computer programinstructions that determine a set of one or more vulnerability detectionstrategies determine a strategy for vulnerability detection that,relative to at least one other strategy for vulnerability detection, isoptimized based on the types of data supported by the set of datasources.
 11. The apparatus as described in claim 7 wherein the computerprogram instructions that determine a set of one or more vulnerabilitydetection strategies determine a strategy for vulnerability detectionthat, relative to at least one other strategy for vulnerabilitydetection, is optimized based on an operating environment in which thesecurity vulnerabilities are to be detected.
 12. The apparatus asdescribed in claim 7 wherein the IAM system is associated with amulti-tenant cloud compute environment, and wherein a vulnerabilitydetection strategy for a first tenant is distinct from a vulnerabilitydetection strategy for a second tenant.
 13. A computer program productin a non-transitory computer readable medium for use in a dataprocessing system, the computer program product holding computer programinstructions which, when executed by the data processing system,facilitate detection of security vulnerabilities in accounts provisionedin an identity and access management (IAM) system, the computer programinstructions operative to: determine types of data supported by a set ofdata sources; based on the types of data supported by the set of datasources, determine a set of one or more vulnerability detectionstrategies to apply to detect the security vulnerabilities; based on theset of one or more vulnerability detection strategies, collect data fromthe data sources, wherein during data collection a given data source ofthe set of data sources is invoked just once to collect data for all ofthe set of one or more vulnerability detection strategies; based on thedata collected, execute the set of one or more vulnerability detectionstrategies; and update at least one vulnerability detection strategy asthe set of data sources is changed or updated.
 14. The computer programproduct as described in claim 13 wherein first and second data sourcesof the set of data sources provide distinct types of data from oneanother.
 15. The computer program product as described in claim 13wherein the types of data include one of: live data, static data, and acombination of live and static data.
 16. The computer program product asdescribed in claim 13 wherein the computer program instructions thatdetermine a set of one or more vulnerability detection strategiesdetermine a strategy for vulnerability detection that, relative to atleast one other strategy for vulnerability detection, is optimized basedon the types of data supported by the set of data sources.
 17. Thecomputer program product as described in claim 13 wherein the computerprogram instructions that determine a set of one or more vulnerabilitydetection strategies determine a strategy for vulnerability detectionthat, relative to at least one other strategy for vulnerabilitydetection, is optimized based on an operating environment in which thesecurity vulnerabilities are to be detected.
 18. The computer programproduct as described in claim 13 wherein the IAM system is associatedwith a multi-tenant cloud compute environment, and wherein avulnerability detection strategy for a first tenant is distinct from avulnerability detection strategy for a second tenant.